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Shogun (toolbox) – open-source, large-scale machine learning toolbox that provides several SVM (Support Vector Machine) implementations (like libSVM, SVMlight) under a common framework and interfaces to Octave, MATLAB, Python, R; Simfit – simulation, curve fitting, statistics, and plotting; SOCR
Curve fitting [1] [2] is the process of constructing a curve, or mathematical function, that has the best fit to a series of data points, [3] possibly subject to constraints. [ 4 ] [ 5 ] Curve fitting can involve either interpolation , [ 6 ] [ 7 ] where an exact fit to the data is required, or smoothing , [ 8 ] [ 9 ] in which a "smooth ...
MATLAB allows matrix manipulations, plotting of functions and data, implementation of algorithms, creation of user interfaces, and interfacing with programs written in other languages. Although MATLAB is intended primarily for numeric computing, an optional toolbox uses the MuPAD symbolic engine allowing access to symbolic computing abilities.
TableCurve 2D is a linear and non-linear Curve fitting software package for engineers and scientists that automates the curve fitting process and in a single processing step instantly fits and ranks 3,600+ built-in frequently encountered equations enabling users to easily find the ideal model to their 2D data within seconds.
R – the stats package includes ar function; [14] the astsa package includes sarima function to fit various models including AR. [15] MATLAB – the Econometrics Toolbox [16] and System Identification Toolbox [17] include AR models. [18] MATLAB and Octave – the TSA toolbox contains several estimation functions for uni-variate, multivariate ...
Consider a set of data points, (,), (,), …, (,), and a curve (model function) ^ = (,), that in addition to the variable also depends on parameters, = (,, …,), with . It is desired to find the vector of parameters such that the curve fits best the given data in the least squares sense, that is, the sum of squares = = is minimized, where the residuals (in-sample prediction errors) r i are ...
The result of fitting a set of data points with a quadratic function Conic fitting a set of points using least-squares approximation. In regression analysis, least squares is a parameter estimation method based on minimizing the sum of the squares of the residuals (a residual being the difference between an observed value and the fitted value provided by a model) made in the results of each ...
The characteristic S-shaped sigmoid curve is obtained with only for integers n ≥ 1. The order of the polynomial in the general smoothstep is 2 n + 1. With n = 1, the slopes or first derivatives of the smoothstep are equal to zero at the left and right edge ( x = 0 and x = 1), where the curve is appended to the constant or saturated levels.